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LAPACKE_sgesvd Example Program in C for Row Major Data Layout
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/*
LAPACKE_sgesvd Example.
=======================
Program computes the singular value decomposition of a general
rectangular matrix A:
8.79 9.93 9.83 5.45 3.16
6.11 6.91 5.04 -0.27 7.98
-9.15 -7.93 4.86 4.85 3.01
9.57 1.64 8.83 0.74 5.80
-3.49 4.02 9.80 10.00 4.27
9.84 0.15 -8.99 -6.02 -5.31
Description.
============
The routine computes the singular value decomposition (SVD) of a real
m-by-n matrix A, optionally computing the left and/or right singular
vectors. The SVD is written as
A = U*SIGMA*VT
where SIGMA is an m-by-n matrix which is zero except for its min(m,n)
diagonal elements, U is an m-by-m orthogonal matrix and VT (V transposed)
is an n-by-n orthogonal matrix. The diagonal elements of SIGMA
are the singular values of A; they are real and non-negative, and are
returned in descending order. The first min(m, n) columns of U and V are
the left and right singular vectors of A.
Note that the routine returns VT, not V.
Example Program Results.
========================
LAPACKE_sgesvd (row-major, high-level) Example Program Results
Singular values
27.47 22.64 8.56 5.99 2.01
Left singular vectors (stored columnwise)
-0.59 0.26 0.36 0.31 0.23
-0.40 0.24 -0.22 -0.75 -0.36
-0.03 -0.60 -0.45 0.23 -0.31
-0.43 0.24 -0.69 0.33 0.16
-0.47 -0.35 0.39 0.16 -0.52
0.29 0.58 -0.02 0.38 -0.65
Right singular vectors (stored rowwise)
-0.25 -0.40 -0.69 -0.37 -0.41
0.81 0.36 -0.25 -0.37 -0.10
-0.26 0.70 -0.22 0.39 -0.49
0.40 -0.45 0.25 0.43 -0.62
-0.22 0.14 0.59 -0.63 -0.44
*/
#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"
#define min(a,b) ((a)>(b)?(b):(a))
/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda );
/* Parameters */
#define M 6
#define N 5
#define LDA N
#define LDU M
#define LDVT N
/* Main program */
int main() {
/* Locals */
MKL_INT m = M, n = N, lda = LDA, ldu = LDU, ldvt = LDVT, info;
float superb[min(M,N)-1];
/* Local arrays */
float s[N], u[LDU*M], vt[LDVT*N];
float a[LDA*M] = {
8.79f, 9.93f, 9.83f, 5.45f, 3.16f,
6.11f, 6.91f, 5.04f, -0.27f, 7.98f,
-9.15f, -7.93f, 4.86f, 4.85f, 3.01f,
9.57f, 1.64f, 8.83f, 0.74f, 5.80f,
-3.49f, 4.02f, 9.80f, 10.00f, 4.27f,
9.84f, 0.15f, -8.99f, -6.02f, -5.31f
};
/* Executable statements */
printf( "LAPACKE_sgesvd (row-major, high-level) Example Program Results\n" );
/* Compute SVD */
info = LAPACKE_sgesvd( LAPACK_ROW_MAJOR, 'A', 'A', m, n, a, lda,
s, u, ldu, vt, ldvt, superb );
/* Check for convergence */
if( info > 0 ) {
printf( "The algorithm computing SVD failed to converge.\n" );
exit( 1 );
}
/* Print singular values */
print_matrix( "Singular values", 1, n, s, 1 );
/* Print left singular vectors */
print_matrix( "Left singular vectors (stored columnwise)", m, n, u, ldu );
/* Print right singular vectors */
print_matrix( "Right singular vectors (stored rowwise)", n, n, vt, ldvt );
exit( 0 );
} /* End of LAPACKE_sgesvd Example */
/* Auxiliary routine: printing a matrix */
void print_matrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda ) {
MKL_INT i, j;
printf( "\n %s\n", desc );
for( i = 0; i < m; i++ ) {
for( j = 0; j < n; j++ ) printf( " %6.2f", a[i*lda+j] );
printf( "\n" );
}
}
Parent topic: SGESVD Example